The World Development Indicators (WDI) is the primary global database of the World Bank for monitoring and comparing development outcomes across 200 countries and over time. It is a time-series dataset which includes over 1,600 indicators, covering the economic, social, environmental, demographic, and institutional dimensions of development.

There are many economic theories explaining the correlation between country income indicators (GDP per capita, country income classification, etc.) and health-related indicators (life expectancy, fertility rate, infant mortaility rate, etc.). At the macroeconomic level are the Preston curve and Endogenous Growth theory. First, the Preston Curve (1975) illustrates the positive but concave relationship between GDP per capita and life expectancy, showing that richer countries generally live longer, but with diminishing returns: income gains matter more at lower income levels, while at higher levels, other factors like medical advances cause bigger leaps in longevity. It was also theorized and supported by reseach that the entire curve moves outward (meaning longer life expectancies for the same income), due to major improvements in public health, education and nutrition. Second, the endogenous growth theory (Lucas [1988] being one of the theorists) explains that growth is driven by human capital accumulation and that health improvements increase labor supply and innovation and increases returns to education, and in the long run, sustains economic growth.

At the microeconomic level, Grossman (1972) wrote on the demand for health wherein, in gist, he explains that there is utility derived from being healthy and living longer. Hence, income is spent (considered as investment) in health products and services such as healthcare, medical products and services, nutrition, exercise, and education. Higher income per capita means possible higher allocation to investments in health, hence, raising life expectancy. Finally, also at the household level, Becker (1961) and Schultz (1962), theorists of human capital, explained that health is considered a component of human capital and is considered a driver of productivity and hence, in the long run, a driver of income.

The graph only covers trends between GDP per capita and life expectancy for years 2005 to 2024. As seen in the graph, GDP per capita and life expectancy has an positive relationship. The curve is rather concave suggesting an increasing life expectancy as income increases but at a diminishing rate. However, this trend is not at all observed when you examine per continent (in the legend, you can examine a continent by deselecting the other continents). Some continents have flat lines or scattered lines. This suggests that the relationship between GDP per capita and life expectancy is not clear. For non-concave lines, they suggest that higher income does not clearly translate to increased life expectancies and vice versa.
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│ Top 10 Life Expectancy (2005)   │ Top 10 Life Expectancy (2023)   │
╞═════════════════════════════════╪═════════════════════════════════╡
│ Monaco                          │ Monaco                          │
├─────────────────────────────────┼─────────────────────────────────┤
│ Andorra                         │ San Marino                      │
├─────────────────────────────────┼─────────────────────────────────┤
│ Japan                           │ Hong Kong SAR, China            │
├─────────────────────────────────┼─────────────────────────────────┤
│ San Marino                      │ French Polynesia                │
├─────────────────────────────────┼─────────────────────────────────┤
│ Hong Kong SAR, China            │ Switzerland                     │
├─────────────────────────────────┼─────────────────────────────────┤
│ Iceland                         │ Japan                           │
├─────────────────────────────────┼─────────────────────────────────┤
│ Macao SAR, China                │ Andorra                         │
├─────────────────────────────────┼─────────────────────────────────┤
│ Switzerland                     │ Spain                           │
├─────────────────────────────────┼─────────────────────────────────┤
│ Australia                       │ Italy                           │
├─────────────────────────────────┼─────────────────────────────────┤
│ Italy                           │ Malta                           │
╘═════════════════════════════════╧═════════════════════════════════╛
In this section, we rank the top 10 countries in life expectancy. As seen in this table, only 7 out of 10 countries in the top 10 for 2005 remained in 2023. This goes to show that over the years, life expectancy may improve or worsen due to a multitude of factors, one major factor being GDP per capita.
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│ Bottom 10 Life Expectancy (2005)   │ Bottom 10 Life Expectancy (2023)   │
╞════════════════════════════════════╪════════════════════════════════════╡
│ Lesotho                            │ Nigeria                            │
├────────────────────────────────────┼────────────────────────────────────┤
│ Eswatini                           │ Chad                               │
├────────────────────────────────────┼────────────────────────────────────┤
│ Zimbabwe                           │ Lesotho                            │
├────────────────────────────────────┼────────────────────────────────────┤
│ Central African Republic           │ Central African Republic           │
├────────────────────────────────────┼────────────────────────────────────┤
│ Sierra Leone                       │ Somalia, Fed. Rep.                 │
├────────────────────────────────────┼────────────────────────────────────┤
│ Chad                               │ Mali                               │
├────────────────────────────────────┼────────────────────────────────────┤
│ Nigeria                            │ Guinea                             │
├────────────────────────────────────┼────────────────────────────────────┤
│ Somalia, Fed. Rep.                 │ Benin                              │
├────────────────────────────────────┼────────────────────────────────────┤
│ Zambia                             │ Burkina Faso                       │
├────────────────────────────────────┼────────────────────────────────────┤
│ Angola                             │ Niger                              │
╘════════════════════════════════════╧════════════════════════════════════╛
In this section, we rank the bottom 10 countries in life expectancy, and compare it to two time periods (2005 and 2023). As seen in this table, only 5 out of 10 countries in the bottom 10 for 2005 remained in 2023. This goes to show that over the years, life expectancy may improve or worsen due to a multitude of factors, one major factor being GDP per capita.
In this section, we examine the minimum, maximum, mean, and standard deviation in life expectancy when categorized according to income classifications for the year 2023.
In this section, we examine the trend between fertility rate and GDP per capita faceted across the continents for year 2023. As seen in the graph, there is a negative relationship between fertility rate and GDP per capita; as GDP per capita increases, the fertility rate is lower. However, across the continents, one can see variations in terms of the steepness of the line. For example, in Europe, the line is very flat, meaning fertility rate remains low in spite of increase in GDP per capita. On the other hand, in Africa, it is very steep, meaning a faster response of the fertility rate to decline as GDP per capita increases.
In this section, we examine the minimum, maximum, mean, and standard deviation in fertility rate when categorized according to income classifications for the year 2023. As seen in the graph, low income countries have a higher average fertility rate, and there is significant variation within the income group, with the mean above 4 births. Lower middle income countries have lower average fertility rate (3 births) but still significant variation in fertility rate within income group. Upper middle income have, again much lower average fertility rate (2 births). Finally, high income countries have lower standard deviation and lower mean fertility rate (1.5 births).
In this section, we examine the average infant mortality rate when categorized according to income classifications for the year 2023. Infant mortality rate is the number of infants who die before reaching age 1, per 1000 live births in a given year. As seen in the graph, low income countries have a higher average infant mortality rate, at 46 per 1000 live births. it is a stark contrast to the infant mortality rate in high income countries, at 5 per 1000 live births. These numbers suggest weak health systems and living conditions in countries with lower income classification.